Provides functions to apply spatial fuzzy unsupervised classification, visualize and interpret results. This method is well suited when the user wants to analyze data with a fuzzy clustering algorithm and to account for the spatial dimension of the dataset. In addition, indexes for estimating the spatial consistency and classification quality are proposed. The methods were originally proposed in the field of brain imagery (seed Cai and al. 2007 <doi:10.1016/j.patcog.2006.07.011> and Zaho and al. 2013 <doi:10.1016/j.dsp.2012.09.016>) and recently applied in geography (see Gelb and Apparicio <doi:10.4000/cybergeo.36414>).
Version: 0.3.4 Depends: R (≥ 3.5) Imports: ggplot2 (≥ 3.2.1), tmap (≥ 3.3-1), spdep (≥ 1.1.2), reldist (≥ 1.6.6), dplyr (≥ 0.8.3), fclust (≥ 2.1.1), fmsb (≥ 0.7.0), future.apply (≥ 1.4.0), progressr (≥ 0.4.0), reshape2 (≥ 1.4.4), stats (≥ 3.5), grDevices (≥ 3.5), shiny (≥ 1.6.0), sf (≥ 1.0-6), leaflet (≥ 2.1.1), plotly (≥ 4.9.3), Rdpack (≥ 2.1.1), matrixStats (≥ 0.58.0), methods (≥ 3.5), terra (≥ 1.6-47), Rcpp (≥ 1.0.6) LinkingTo: Rcpp, RcppArmadillo Suggests: knitr (≥ 1.28), rmarkdown (≥ 2.1), markdown (≥ 1.1), future (≥ 1.16.0), ppclust (≥ 1.1.0), ClustGeo (≥ 2.0), car (≥ 3.0-7), rgl (≥ 0.100), ggpubr (≥ 0.2.5), RColorBrewer (≥ 1.1-2), kableExtra (≥ 1.1.0), viridis (≥ 0.5.1), testthat (≥ 3.0.0), bslib (≥ 0.2.5), shinyWidgets (≥ 0.6), shinyhelper (≥ 0.3.2), waiter (≥ 0.2.2), classInt (≥ 0.4-3), covr Published: 2023-09-12 DOI: 10.32614/CRAN.package.geocmeans Author: Jeremy Gelb [aut, cre], Philippe Apparicio [ctb] Maintainer: Jeremy Gelb <jeremy.gelb at ucs.inrs.ca> BugReports: https://github.com/JeremyGelb/geocmeans/issues License: GPL-2 URL: https://github.com/JeremyGelb/geocmeans NeedsCompilation: yes SystemRequirements: C++17 Language: en-CA Citation: geocmeans citation info Materials: README NEWS CRAN checks: geocmeans results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=geocmeans to link to this page.
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